FLORIDA: Fake-looking Real Images Dataset
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Abstract (arXiv)
Although extensive research has been carried out to evaluate the effectiveness of AI tools and models in detecting deep fakes, the question remains unanswered regarding whether these models can accurately identify genuine images that appear artificial. In this study, as an initial step towards addressing this issue, we have curated a dataset of 510 genuine images that exhibit a fake appearance and conducted an assessment using two AI models. We show that two models exhibited subpar performance when applied to our dataset. Additionally, our dataset can serve as a valuable tool for assessing the ability of deep learning models to comprehend complex visual stimuli. We anticipate that this research will stimulate further discussions and investigations in this area. Our dataset is accessible at https://github.com/aliborji/FLORIDA.
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References · 9
- 2023Segment Anythingcited by 8,234
- 2023A Survey on Multimodal Large Language Modelscited by 909
- 2020What makes fake images detectable? Understanding properties that generalizecited by 273
- 2020DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detectioncited by 233
- 2020Media Forensics and DeepFakes: an overviewcited by 209
- 2019Deep Learning for Deepfakes Creation and Detection: A Surveycited by 102
- 2022Generated Faces in the Wild: Quantitative Comparison of Stable Diffusion, Midjourney and DALL-E 2cited by 55
- 2020DeepFake Detection: Current Challenges and Next Stepscited by 44
- 2023Qualitative Failures of Image Generation Models and Their Application in Detecting Deepfakescited by 31
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